In a 50 to 100+ microservice environment with dense service-to-service dependencies, even small regressions can cascade silently. And slowing down isn’t an option. Leadership needs faster delivery and fewer incidents. This is why we built Reliability Delta.
Originally posted as a livestream from OllyGarden.
Originally posted to TFIR by Monika Chauhan. Causely’s Severin Neumann explains how causal reasoning, MCP, and AI-driven automation are transforming SRE workflows and Kubernetes reliability.
Originally posted to Techstrong.tv. Learn how Causely integrates reliability engineering into product development, tackling challenges in cloud-native applications.
With community-standard instrumentation and the OTel Collector, your metrics, logs, and traces are no longer trapped in a walled garden. Originally posted to the ClickHouse blog.
Originally posted to International Business Times by David Thompson.
Learn why causal inference is the missing piece in AI-driven observability, and how Causely is the only AI SRE platform that uses causal reasoning to pinpoint where, what, and why application and system related issues occur.
Originally posted to Cloud Native Now by Mike Vizard.
Reposted from its original publication on TechTimes by Carl Williams
Causely announced the launch of the Causely MCP Server that seamlessly integrates into any MCP-compatible IDE and enables developers to automatically diagnose, understand, and remediate complex issues within Kubernetes and application code using natural language prompts.
The Causely MCP Server brings our Causal Reasoning Engine directly into the IDE so engineers can understand why incidents happen and apply the right fix at the right layer, whether that’s runtime, configuration, or code.
Causely now leverages Google’s Gemini models to enhance how users interact with its Causal Reasoning Engine.